• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.447-450
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• 2013

This paper proposes the way to prevent drowsy driving by recognizing drivers eyes and yawn using a front camera. The method uses the Viola-Jones algorithm to detect eyes area and mouth area from detection face region. In the eyes area, it uses the Hough transform to recognize eye circle in order to distinguish drowsy driving. In the mouth area, it determines whether for the driver to yawn through a sub-window testing by applying a HSV-filter and detecting skin color of the tongue. The test result shows that the recognition rate of yawn reaches up to 90%. It is expected that the method introduced in this paper might contribute to reduce the number of drowsy driving accidents.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.174-183
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• 2011

This paper is about a bar code decoding algorithm developed for smart phone applications. The algorithm consists of bar code data extraction procedure, bar code signal estimation procedure, and bar code decoding procedure. To detect the peak bar code module, a DSTW had been applied because of its outstanding performance in ECG peak detection. In order to minimize errors due to non-uniform light effect, the proposed algorithm was acted as a baseline wandering filter based on module peaks detection. The algorithm had been tested to evaluate the performance under the conditions of blurring, non-uniformed light and white noises. The algorithm had shown excellent performance in reconstruction of bar code decoding, compared to other conventional methods. In order to show the possibility of applying the algorithm to a smart phone, a real UPC-A type 150 bar code pictures obtained from a smart phone camera was applied to the algorithm, achieving the correct recognition rate of 97.33%.

• Convergence Security Journal
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• v.8 no.4
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• pp.135-143
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• 2008

Currently, The HMI system is being used on the network is limited in the ability. In this paper, an Industrial HMI applied the transformed state splitting algorithm. this study suggests by applying a transformed the Successive state splitting algorithm, for the modeling in the questions of the expected data. So, you can save time and reliable and precise as high as 98.15 percent repregented recognition rate. HMI system applied to the voice of industrial equipment the man can not act directly in the industry environment was able to drive devices. Optimize the performance of the engine was the voice of HMI system.

• Journal of agricultural medicine and community health
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• v.17 no.2
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• pp.113-121
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• 1992

In order to estimate the pattern of medical care utilization and recognition for health factor among the inhabitants in Wan-do district which is located off the southern seashore from mainland Korea, household interview survey was performed from January 15 to 30, 1990 in Wan-do Gun area. The results observed were following: 1. Among the users of medical facilities 40.8% used public health facility as first contact facility. Lower the income level was and longer the residency duration was, the utilization rate of public health facilities was higher. By age groups and medical security status the utilization pattern was likely to disperse to local clinic and secondary contact medical resources. 2. Medical expense and access time were significantly different between primary contact and secondary contact medical resources. 3. Public health facility was recognized as the favoured institute having advantage of geographic and economic accessibility. 4. Statistically significant determinants in public health facility utilization among total medical service were the region, the medical expense, and the access time.

• The Journal of the Acoustical Society of Korea
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• v.24 no.5
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• pp.255-261
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• 2005

In this paper. experiments are conducted to extract a set of non-Parametric warping functions to examine the characteristics of the warping among speakers' utterances. For this Purpose. we made use of MFCC and LP spectra of vowels in choosing reference spectrum of each vowel as well as representative spectra of each speaker. These spectra are compared by DTW to give the warping functions of each speaker. The set of warping functions are then defined by clustering the warping functions of all the speakers. Noting that male and female warping functions have shapes similar to Piecewise linear function and Power function respectively, a new hybrid set of warping functions is defined. The effectiveness of the extracted warping functions are evaluated by conducting phone level recognition experiments, and improvements in accuracy rate are observed in both warping functions.

• The Journal of the Acoustical Society of Korea
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• v.22 no.5
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• pp.403-407
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• 2003

Recently, eigenvoice approach has been widely used for rapid speaker adaptation. However, even in the eigenvoice approach, Performance improvement using very small amount of adaptation data is relatively small in comparison with that using somewhat large adaptation data because the reliable estimation of weights of eigenvoice is difficult. In this paper, we propose a rapid speaker adaptation method based on eigenvoice using the weight distribution characteristics to improve the performance on a small adaptation data. In the Experimental results on vocabulary-independent word recognition task (using PBW 452 database), the weight threshold method alleviates the problem of relatively low performance for a tiny small adaptation data. When single adaptation word is used, word error rate is reduced about 9-18% by the weight threshold method.

• Journal of Information Processing Systems
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• v.8 no.3
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• pp.399-408
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• 2012

Hand gesture recognition is an important area of research in the field of Human Computer Interaction (HCI). The geometric attributes of the hand play an important role in hand shape reconstruction and gesture recognition. That said, fingertips are one of the important attributes for the detection of hand gestures and can provide valuable information from hand images. Many methods are available in scientific literature for fingertips detection with an open hand but very poor results are available for fingertips detection when the hand is closed. This paper presents a new method for the detection of fingertips in a closed hand using the corner detection method and an advanced edge detection algorithm. It is important to note that the skin color segmentation methodology did not work for fingertips detection in a closed hand. Thus the proposed method applied Gabor filter techniques for the detection of edges and then applied the corner detection algorithm for the detection of fingertips through the edges. To check the accuracy of the method, this method was tested on a vast number of images taken with a webcam. The method resulted in a higher accuracy rate of detections from the images. The method was further implemented on video for testing its validity on real time image capturing. These closed hand fingertips detection would help in controlling an electro-mechanical robotic hand via hand gesture in a natural way.

• Proceedings of the KIEE Conference
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• 2005.07c
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• pp.2223-2225
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• 2005

In this work, experimental investigation has been mainly done. For this purpose, UHF sensor has been designed and fabricated to detect the partial discharges produced from the 10 artificial defects introduced into the real scale 70kV GIS mock-up under the high voltage at the well shielded room. And also, in order to verify the applicability of the proposed method at the site, the proposed CAPD (chaos analysis of partial discharge) is combined with spectral analysis method in order to identify the nature of the above 10 defects. The PD pattern recognition of each defect has been fulfilled by applying self developed artificial neural network soft ware. The result shows that the recognition rate is reached to be 80% by newly proposed method while the traditional PRPD analysis method leads us to obtain 41%. In consequence, it can be pointed out that the proposed method seems likely to be applicable to the real GIS at the site.

• Journal of Navigation and Port Research
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• v.29 no.9
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• pp.789-793
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• 2005

The container terminals in Korea usually adopts both the bar code and the image recognition systems at the gate complex to capture necessary information on containers passing through the gate. With the rapid advancement of Information Technology(IT) these systems, however, seem to make the user not satisfied due to the inherent limitations such as the long process time taken, low rate of recognition etc., This paper, therefore, examines the adoption of Radio Frequency Identification (RFID) technology to container terminals, and tried to get some implication for the way to improve the productivity of the terminal. The results imply that some improvement in the gate and storage yard operation is feasible by the benefit of using the information of vehicles and containers collected in advance by RFID technology.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2036-2038
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• 2001

In this paper, we propose the neural network based emotion recognition method for intelligently recognizing the human's emotion using vision system. In the proposed method, human's emotion is divided into four emotion (surprise, anger, happiness, sadness). Also, we use R,G,B(red, green, blue) color image data and the gray image data to get the highly trust rate of feature point extraction. For this, we propose an algorithm to extract four feature points (eyebrow, eye, nose, mouth) from the face image acquired by the color CCD camera and find some feature vectors from those. And then we apply back-prapagation algorithm to the secondary feature vector(position and distance among the feature points). Finally, we show the practical application possibility of the proposed method.